update app.py

app.py

@@ -3,8 +3,11 @@ import json
 import ee
 import geemap
 import os
+import time
 import pandas as pd
+import geopandas as gpd
 from datetime import datetime
+from shapely.geometry import Point
 
 # Set up the page layout
 st.set_page_config(layout="wide")
@@ -56,18 +59,6 @@ custom_formula = ""
 if index_choice == 'Custom Formula':
     custom_formula = st.text_input("Enter Custom Formula (e.g., 'B5 - B4 / B5 + B4')")
 
-# Show Cloud Pixel Percentage option if NDVI or NDWI is selected
-cloud_threshold = None
-if index_choice in ['NDVI', 'NDWI']:
-    cloud_threshold = st.slider(
-        "Set Cloud Pixel Percentage Threshold",
-        min_value=0,
-        max_value=100,
-        value=20,
-        step=1,
-        help="Cloud coverage threshold (in percentage) to mask out cloud pixels."
-    )
-
 # Function to read points from CSV
 def read_csv(file_path):
     df = pd.read_csv(file_path)
@@ -190,11 +181,10 @@ if locations_df is not None:
         # Define the region of interest (ROI) using the current latitude and longitude
         roi = ee.Geometry.Point([longitude, latitude])
 
-        # Load the image collection based on the user's selection
-        collection = ee.ImageCollection('COPERNICUS/S2') \
+        # Load Sentinel-2 image collection
+        collection = ee.ImageCollection(sub_options[sub_selection]) \
             .filterDate(ee.Date(start_date_str), ee.Date(end_date_str)) \
-            .filterBounds(roi) \
-            .filter(ee.Filter.lt('system:cloud_coverage', cloud_threshold))  # Apply cloud coverage filter
+            .filterBounds(roi)
 
         # Check if the collection has images for the selected date range
         image_count = collection.size().getInfo()
@@ -202,6 +192,7 @@ if locations_df is not None:
             st.warning(f"No images found for {location_name}.")
         else:
             st.write(f"Found {image_count} images for {location_name}.")
+
             image = collection.first()
 
             # Perform calculation based on user selection
@@ -210,12 +201,19 @@ if locations_df is not None:
             elif index_choice == 'NDWI':
                 result = calculate_ndwi(image, roi)
             elif index_choice == 'Average NO₂':
-                result = calculate_avg_no2_sentinel5p(image, roi)
+                # Check if NO2 is available in the current dataset (Sentinel-2 does not have NO2)
+                if 'NO2' in image.bandNames().getInfo():
+                    result = calculate_avg_no2_sentinel5p(image, roi)
+                else:
+                    st.warning(f"No NO2 band found for {location_name}. Please use Sentinel-5P for NO₂ data.")
+                    result = None
             elif index_choice == 'Custom Formula' and custom_formula:
                 result = calculate_custom_formula(image, roi, custom_formula)
 
             if result:
                 st.write(f"Result for {location_name}: {result.getInfo()}")
+
+                # Add the result to a list for output
                 results.append({'Location': location_name, 'Result': result.getInfo()})
 
 # Convert results to DataFrame for download